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- #!/usr/bin/env python3
- from PIL import Image
- import numpy as np
- # === CONFIG ===
- INPUT_IMAGE = "t.png"
- OUTPUT_SCAD = "output.scad"
- PIXEL_SIZE = 1 # mm per pixel (X and Y)
- MAX_HEIGHT = 10.0 # max Z height in mm
- DOWNSCALE = 3 # Skip every N pixels for speed (set to 1 for full res)
- # Full res will result in very long openscad load times
- # === LOAD AND PROCESS IMAGE ===
- img = Image.open(INPUT_IMAGE).convert("L")
- data = np.array(img)
- # Optionally downscale to speed up output
- data = data[::DOWNSCALE, ::DOWNSCALE]
- # Normalize grayscale to height
- zscale = MAX_HEIGHT / 255.0
- heights = data * zscale
- rows, cols = heights.shape
- # === WRITE SCAD FILE ===
- with open(OUTPUT_SCAD, "w") as f:
- f.write("// Generated by img2scad.py\n")
- f.write("union() {\n")
- for y in range(rows):
- for x in range(cols):
- h = heights[y, x]
- if h > 0:
- # OpenSCAD coordinate system: [x, y, z]
- f.write(f" translate([{x * PIXEL_SIZE}, {y * PIXEL_SIZE}, 0])\n")
- f.write(f" cube([{PIXEL_SIZE}, {PIXEL_SIZE}, {h:.2f}]);\n")
- f.write("}\n")
- print(f"Done. Output written to: {OUTPUT_SCAD}")
- '''
- Notes:
- openSCAD will take forever to load a prebuilt complex openscad file IF you load that object from the start.
- (even if you have manifold selected in the rendering options of developer mode)
- (becuase init still uses CSG regardless)
- The work around is to load a blank output file, then generate the data using this script.
- then, provided you have manifold selected, reloading the data will be much faster.
- 2. This is true, to 200K objects. at over 200K objects, openscad will default to CSG modeling, which is the same
- as being broken.
- 3. background subtraction concept forgoing complex image processing:
- for h < some min_hight
- render no objects.
- this may help keep object count low, where you can continue to reap the benifits of manifold rendering.
- h < 3
- but Im pretty tired finding other ppls bugs. Ima go sleep.
- '''
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